Peng Qiu

Associate Professor

Georgia Institute of Technology

United States

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Peng Qiu is an Associate Professor at the Georgia Institute of Technology, USA. His research areas include single-cell RNA sequencing, cellular diversity analysis, and the modulation of endothelial progenitor cell secretomes. Recent publications highlight his work on hierarchical marker gene selection, strategies for integrating multi-batch single-cell data, and quantifying cell-type-specific differences in single-cell datasets.

Articles (15)

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2025

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2024

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2024

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2020

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2020

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2020

Collaborators (5)

Edward A. Botchwey

UNITED STATES

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Vanessa Franco Carvalho Dartora

Georgia Institute of Technology College of Engineering

UNITED STATES

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Marc Fernández Yagüe

Lecturer (Assistant Professor)

Queen Mary University of London

UNITED KINGDOM

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Alyssa Panitch

Georgia Institute of Technology

UNITED STATES

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Denis Tsygankov

Associate Professor

Georgia Institute of Technology

UNITED STATES

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Peng Qiu

Research Interests

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Articles (15)

Extracellular matrix ligands modulate the endothelial progenitor cell secretome for enhanced angiogenesis

Recursive Clustering of Cellular Diversity in scRNA-Seq Data

Gene representation bias in spatial transcriptomics

Quantifying the clusterness and trajectoriness of single-cell RNA-seq data

scDisInFact: disentangled learning for integration and prediction of multi-batch multi-condition single-cell RNA-sequencing data

Hierarchical marker genes selection in scRNA-seq analysis

High cell throughput, programmable fixation reveals the RNA and protein co-regulation with spatially resolved NFκB pseudo-signaling

Identifying dysregulated immune cell subsets following volumetric muscle loss with pseudo-time trajectories

Quantifying Cell-Type-Specific Differences of Single-Cell Datasets Using Uniform Manifold Approximation and Projection for Dimension Reduction and Shapley Additive exPlanations

Domain adaptation for supervised integration of scRNA-seq data

Analyzing immune response to engineered hydrogels by hierarchical clustering of inflammatory cell subsets

JSOM: Jointly-evolving self-organizing maps for alignment of biological datasets and identification of related clusters

Shape-to-graph mapping method for efficient characterization and classification of complex geometries in biological images

Harnessing lipid signaling pathways to target specialized pro-angiogenic neutrophil subsets for regenerative immunotherapy

Embracing the dropouts in single-cell RNA-seq analysis

Collaborators (5)

Edward A. Botchwey

Vanessa Franco Carvalho Dartora

Marc Fernández Yagüe

Alyssa Panitch

Denis Tsygankov

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